83 lines
2.3 KiB
Markdown
83 lines
2.3 KiB
Markdown
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# Assignment 1
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## Part A
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### Append
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```shell
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xsb
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```
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```prolog
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['A/append.P'].
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suffix([1,2], [1,2,3,4]).
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cut([1,2,3]).
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```
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### Reach
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generate input set
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```shell
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python randomgen.py [number of nodes]
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```
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### Transitive closure and cycle
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```shell
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xsb
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```
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```prolog
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['A/cycle.P'].
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path(1,2) .
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cycle(1).
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```
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### N-queens
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```shell
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xsb
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```
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```prolog
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['A/queens.P'].
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timeNQueen(8).
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timeOneQueen(8).
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```
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## Part B
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### Reach
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generate input set
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```shell
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python randomgen.py [number of nodes]
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```
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```shell
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clingo --models 0 B/reach.lp
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```
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| Input size | Way 1 | Way 2 | Way 3 | Way 4 |
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| ---------- | ------- | ------ | ------ | ------ |
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| 10000 | 0.655s | 0.703s | 0.664s | 0.665s |
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| 20000 | 1.376s | 1.446s | 1.290s | 1.292s |
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| 50000 | 3.355s | 3.501s | 2.750s | 1.645s |
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| 100000 | 6.778s | 5.002s | 3.375s | 3.438s |
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| 200000 | 12.119s | 7.514s | 7.267s | 7.021s |
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Though it looks like the Way4 is way better tha Way 1(Almost twice as fast), but if we let the computer to rest for a while and rerun them the other way(start from 4, then 3, follow by 2 and 1), we got
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| Input size | Way 1 | Way 2 | Way 3 | Way 4 |
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| ---------- | ------ | ------ | ------ | ------- |
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| 200000 | 7.146s | 7.610s | 7.120s | 12.103s |
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It is exactly the other way around! I belive it is because the input file becomes too large
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(42 MByte), so it waste a lot of time to load it to memory then cache, and the following ones has much higher cache hits rate, so the first one takes way longer than the others.
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### N-queens
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```shell
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clingo --models 0 B/nqueens.lp
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```
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```shell
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clingo --models 1 B/nqueens.lp
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```
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| Number of queens | Time for 1 queen | Time for all queens |
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| ---------------- | ---------------- | ------------------- |
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| 8 | 0.004s | 0.006s |
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| 10 | 0.003s | 0.086s |
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| 12 | 0.004s | 4.909s |
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| 14 | 0.006s | Too long to run |
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| 20 | 0.011s | |
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| 50 | 0.073s | |
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| 100 | 0.463s | |
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| 200 | 3.233s | |
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| 500 | 35.073s | |
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## Part C
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### N-queens
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